Paper Citation Record · LEDGER

Analyzing Training-Free Corruption Detection for Object Detection Datasets

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.10666.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.10666 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:46:21.603334Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy0
unresolved37
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d2e7c81d-a2ac-469f-a31e-e914ae2b585a · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Emerg- ing properties in self-supervised vision transformers, 2021

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 3f32dc08-bb12-4375-b105-9669f601b3ef · outbound

This paper cites Combating noisy labels in object detection datasets, 2023.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Combating noisy labels in object detection datasets, 2023

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 2293c6be-2f53-45cd-b5c2-bc7eda5d0242 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Analyzing Training-Free Corruption Detection for Object Detection Datasets A Simple Framework for Contrastive Learning of Visual Representations

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-03T04:37:37.247765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7742c953-ffe1-4441-8284-efa9b775fc72 · outbound

This paper cites Instance-dependent label-noise learning with manifold- regularized transition matrix estimation, 2022.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Instance-dependent label-noise learning with manifold- regularized transition matrix estimation, 2022

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 4aff3929-917f-45c0-b014-a0be1ff09076 · outbound

This paper cites Learning with instance-dependent label noise: A sample sieve approach, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Learning with instance-dependent label noise: A sample sieve approach, 2021

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 30b61966-e234-4a99-a094-d6d911d21329 · outbound

This paper cites Instructblip: Towards general- purpose vision-language models with instruction tuning,.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Instructblip: Towards general- purpose vision-language models with instruction tuning,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation c5e72837-638a-4384-9336-62fb2e0967e4 · outbound

This paper cites On the state of data in computer vision: Human annotations remain indis- pensable for developing deep learning models, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets On the state of data in computer vision: Human annotations remain indis- pensable for developing deep learning models, 2021

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation f2147957-2b00-40b1-9895-41f8b852764d · outbound

This paper cites Everingham, L.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Everingham, L

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 2f02d009-7dc2-4022-a612-51b9672effa6 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation effb2d91-f0ad-4d43-9420-40e839b650ae · outbound

This paper cites A survey on dataset quality in ma- chine learning.Information and Software Technology, 162: 107268, 2023.

Analyzing Training-Free Corruption Detection for Object Detection Datasets A survey on dataset quality in ma- chine learning.Information and Software Technology, 162: 107268, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 1198b2e1-eb04-496f-86d0-7ade26360cd6 · outbound

This paper cites How we cleaned up PASCAL and improved mAP by 13%.https://www.edge- ai- vision.com/ 2022/08/how-we-cleaned-up-pascal-and -improved-map-by-13/, 2022.

Analyzing Training-Free Corruption Detection for Object Detection Datasets How we cleaned up PASCAL and improved mAP by 13%.https://www.edge- ai- vision.com/ 2022/08/how-we-cleaned-up-pascal-and -improved-map-by-13/, 2022

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation eecb65db-d845-4efd-a8fe-048468ef238f · outbound

This paper cites Learning with instance- dependent noisy labels by anchor hallucination and hard sample label correction, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Learning with instance- dependent noisy labels by anchor hallucination and hard sample label correction, 2024

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation e5a1573d-096d-4a12-908f-960aa601d52f · outbound

This paper cites Label-noise robust generative adversarial networks, 2019.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Label-noise robust generative adversarial networks, 2019

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation d8308aa9-adbc-451a-b35d-bbe8a54c8fc2 · outbound

This paper cites Learning multiple layers of features from tiny images.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Learning multiple layers of features from tiny images

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 548b5779-19db-4bf6-a55a-5ef59e1f3f96 · outbound

This paper cites Cifar-10 (canadian institute for advanced research).

Analyzing Training-Free Corruption Detection for Object Detection Datasets Cifar-10 (canadian institute for advanced research)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 04f1b755-cdaf-4e8a-a024-933d55551769 · outbound

This paper cites Understanding instance-level label noise: Dis- parate impacts and treatments, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Understanding instance-level label noise: Dis- parate impacts and treatments, 2021

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation fcf7b00d-9645-4a97-97f5-3a990b085e61 · outbound

This paper cites The ef- fect of improving annotation quality on object detection datasets: A preliminary study.

Analyzing Training-Free Corruption Detection for Object Detection Datasets The ef- fect of improving annotation quality on object detection datasets: A preliminary study

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 89c01383-a617-4d8b-9128-380cde5d5614 · outbound

This paper cites Muller and Karla Markert.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Muller and Karla Markert

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation fc4bcadd-943d-4c88-a8b4-40aac028dd53 · outbound

This paper cites Northcutt, Anish Athalye, and Jonas Mueller.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Northcutt, Anish Athalye, and Jonas Mueller

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation f73aa3aa-e7e1-413b-ac4c-0d32a2c9ca95 · outbound

This paper cites Northcutt, Lu Jiang, and Isaac L.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Northcutt, Lu Jiang, and Isaac L

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 31d3d8c0-faa3-40b6-b9e0-ebff4231b0b2 · outbound

This paper cites Kitti vision bench- mark suite.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Kitti vision bench- mark suite

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 84a0dedc-d9a1-411e-9bef-52cf3804237f · outbound

This paper cites Clip: Contrastive language–image pretraining (github repository).https://github.com/openai/ CLIP.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Clip: Contrastive language–image pretraining (github repository).https://github.com/openai/ CLIP

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 8b9ed315-7dab-423a-82f8-7b5c79059e5f · outbound

This paper cites Dinov2: Learning robust visual features with- out supervision, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Dinov2: Learning robust visual features with- out supervision, 2024

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 844c58d7-93f9-4e13-98ae-0df2a974c44c · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Learning transferable visual models from natural language supervision, 2021

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation daff123b-573d-472f-945b-a9821fe11033 · outbound

This paper cites Dino: Self-supervised vision trans- formers (github repository).https://github.com/ facebookresearch/dino.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Dino: Self-supervised vision trans- formers (github repository).https://github.com/ facebookresearch/dino

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 196e5f56-5c87-45c4-8868-a5eccb381976 · outbound

This paper cites An embedding is worth a thousand noisy labels, 2025.

Analyzing Training-Free Corruption Detection for Object Detection Datasets An embedding is worth a thousand noisy labels, 2025

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 54c66f00-79a3-44a2-a10a-c360bd51add2 · outbound

This paper cites Identifying label errors in object detection datasets by loss inspection, 2023.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Identifying label errors in object detection datasets by loss inspection, 2023

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation c883d59d-5c3b-4c5b-9cee-9505846d8ff5 · outbound

This paper cites Cleanlab documentation, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Cleanlab documentation, 2024

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 89dc0acc-dd33-49e3-be54-980f343986c6 · outbound

This paper cites Cleanlab tutorial: Object detection, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Cleanlab tutorial: Object detection, 2024

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 5bb3e343-8c1d-4267-8570-778ea8d8f4c7 · outbound

This paper cites Cleanlab research, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Cleanlab research, 2024

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation f00f4852-8754-4b42-81c4-0793d59dce29 · outbound

This paper cites Objectlab: Automated diagnosis of mislabeled images in ob- ject detection data, 2023.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Objectlab: Automated diagnosis of mislabeled images in ob- ject detection data, 2023

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 8a134b2f-a7ca-445f-9b35-9e5545b0084a · outbound

This paper cites Label con- vergence: Defining an upper performance bound in object recognition through contradictory annotations, 2025.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Label con- vergence: Defining an upper performance bound in object recognition through contradictory annotations, 2025

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 5128a2aa-1707-4479-8fe9-09a4a49bbb85 · outbound

This paper cites Simifeat.https : / / github.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Simifeat.https : / / github

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 455d26cc-6f4b-47a0-917c-e522aa92db0e · outbound

This paper cites Autovdc: Automated vision data cleaning using vision-language models, 2025.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Autovdc: Automated vision data cleaning using vision-language models, 2025

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation c7b46985-2b3a-4144-815e-745fe5b20c51 · outbound

This paper cites Robust early-learning: Hindering the memorization of noisy labels.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Robust early-learning: Hindering the memorization of noisy labels

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation da99963c-a711-4b9b-b98e-83b2dab8cdc7 · outbound

This paper cites Clusterability as an alternative to anchor points when learning with noisy labels, 2021.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Clusterability as an alternative to anchor points when learning with noisy labels, 2021

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation 8cb37bd4-0b18-474b-a8dc-a6e35e71f5c8 · outbound

This paper cites Detecting cor- rupted labels without training a model to predict, 2022.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Detecting cor- rupted labels without training a model to predict, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Observation fb083455-25bd-40ea-939a-ae20825017e1 · outbound

This paper cites Vdc: Versatile data cleanser based on visual- linguistic inconsistency by multimodal large language mod- els, 2024.

Analyzing Training-Free Corruption Detection for Object Detection Datasets Vdc: Versatile data cleanser based on visual- linguistic inconsistency by multimodal large language mod- els, 2024

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-27T13:46:21.603334Z

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Pith citing papers

No inbound Pith citation observations are available.